Source credibility is known as an important prerequisite to ensure effective communication (Pornpitakpan, 2004). Nowadays not only humans but also technological devices such as humanoid robots can communicate with people and can likewise be rated credible or not as reported by Fogg and Tseng (1999). While research related to the machine heuristic suggests that machines are rated more credible than humans (Sundar, 2008), an opposite effect in favor of humans’ information is supposed to occur when algorithmically produced information is wrong (Dietvorst, Simmons, and Massey, 2015). However, humanoid robots may be attributed more in line with humans because of their anthropomorphically embodied exterior compared to non-human-like technological devices. To examine these differences in credibility attributions a 3 (source-type) x 2 (information’s correctness) online experiment was conducted in which 338 participants were asked to either rate a human’s, humanoid robot’s, or non-human-like device’s credibility based on either correct or false communicated information. This between-subjects approach revealed that humans were rated more credible than social robots and smart speakers in terms of trustworthiness and goodwill. Additionally, results show that people’s attributions of theory of mind abilities were lower for robots and smart speakers on the one side and higher for humans on the other side and in part influence the attribution of credibility next to people’s reliance on technology, attributed anthropomorphism, and morality. Furthermore, no main or moderation effect of the information’s correctness was found. In sum, these insights offer hints for a human superiority effect and present relevant insights into the process of attributing credibility to humanoid robots.
CITATION STYLE
Finkel, M., & Krämer, N. C. (2022). Humanoid Robots – Artificial. Human-like. Credible? Empirical Comparisons of Source Credibility Attributions Between Humans, Humanoid Robots, and Non-human-like Devices. International Journal of Social Robotics, 14(6), 1397–1411. https://doi.org/10.1007/s12369-022-00879-w
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